Name
Abstract | ||
|---|---|---|
A condition is a constraint that determines when something holds. Mining them is paramount to understanding many sentences properly. There are a few pattern-based approaches that fall short because the patterns must be handcrafted and it is not easy to characterise unusual ways to express conditions; there is one machine-learning approach that requires specific-purpose dictionaries, taxonomies, and heuristics, works on opinion sentences only, and was evaluated on a small dataset with Japanese sentences on hotels. In this paper, we present an encoder-decoder model to mine conditions that does not have any of the previous drawbacks and outperforms the state of the art in terms of effectiveness. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.5220/0007379506240630 | PROCEEDINGS OF THE 11TH INTERNATIONAL CONFERENCE ON AGENTS AND ARTIFICIAL INTELLIGENCE (ICAART), VOL 2 |
Keywords | Field | DocType |
Condition Mining, Natural Language Processing, Deep Learning, Sequence Labelling | Encoder decoder,Computer science,Heuristics,Artificial intelligence,Deep learning,Machine learning | Conference |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fernando O. Gallego | 1 | 0 | 2.70 |
| Rafael Corchuelo | 2 | 389 | 49.87 |